1) 16S amplicons

1.1) Data overview

The dataset “Taraspina 18S miTags” contains reads from 122 samples of Malaspina. On average, each sample contains 45940 OTUs:

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##     405   20410   33100   45940   68340  148200


Overall reads per sample:

1.2) Normalization


In order to keep as many samples as possible, we rarefy at 16509 reads per sample. By that, we loose 31 samples, and after removing the exluded samples in the 18S dataset (to make them comparable), we end up with a normalized dataset containing 91 samples and 8881 OTUs.


Datasets summary:

dim(tb16_tax) #original dataset
## [1] 9114  128
dim(tb16_tax_occur) #original dataset with occurrence data alone
## [1] 9114  122
dim(tb16_tax_occur_min16509) #dataset without samples with less than 16509 OTUs
## [1] 8881   91
dim(tb16_tax_occur_ss16509_no_cero) #rarefied dataset
## [1]   91 8173

1.3) General community analysis

1.3.1) Richness and evenness (Shannon index)

Most of the samples take Shannon Index values between 2.5 and 3.5:

1.3.2) Richness: OTU number

Lowest number of OTUs per sample:

## [1] 618

Maximum number of OTUs per sample:

## [1] 1660

In most of the samples, we can identify about 1400 OTUs:

1.3.3) Index of evenness

1.3.3.1) Pielou’s index

The Pielou index (constrained between 0 and 1) takes values closer to 1 as the variation of species proportion in a sample increases. Our samples get values around 0.6, meaning that the numerical composition of different OTUs in a sample is not so variable - we might observe certain dominant species.

1.3.4) Abundance Models

Most of the OTUs show very few occurrences, suggesting that we will probably be able to identify a significant ammount of rare otus:

1.3.4.1) Rank-Abundance or Dominance/Diversity Model (“radfit”)

The OTUs abundance distribution fits relativelly close to log-normal model.

1.3.4.2) Preston’s Lognormal Model

According to Preston’s lognormal model fit into species frequencies groups, we’re missing ~262 species:

veiledspec(tb16_tax_occur_ss16509_prestonfit)
## Extrapolated     Observed       Veiled 
##    9143.6079    8881.0000     262.6079


When computing Prestons’ lognormal model fit without pooling data into groups, we miss ~251 species:

## Extrapolated     Observed       Veiled 
##    9132.6917    8881.0000     251.6917

1.3.5) Rarefaction curves of rarefied and non-rarefied datasets

1.3.6) Beta diversity

1.3.6.1) Dissimilarity matrix using Bray-Curtis index:

The Bray-Curtis dissimilarity, constrained between 0 (minimum distance) and 1 (highest dissimilarity) allows us to quantify the differences between samples according to the composition and relative abundance of their OTUs. In our dataset, most of the samples pairs take dissimilarity values between between 2 and 4, meaning that their composition is substantially similar.

1.3.6.2) Hierarchical clustering

The stations seem to form clusters according to geographic localization, but there are no evident clusters separated from the general groups.

(To be done: assign Longhurst provinces information to each station and check if any of the central clusters is meaningful regarding to the samples’ geographical location)

1.3.6.3) Non-metric multidimensional scaling

We can identify a prominent group in the central part of the NMDS plot and a few outliers in the central-high edge of the plot. The stress parameter takes a value below 0.2, suggesting that the plot is acceptable.

## 
## Call:
## monoMDS(dist = tb16_tax_occur_ss16509_no_cero.bray) 
## 
## Non-metric Multidimensional Scaling
## 
## 91 points, dissimilarity 'bray', call 'vegdist(x = tb16_tax_occur_ss16509_no_cero, method = "bray")'
## 
## Dimensions: 2 
## Stress:     0.1477793 
## Stress type 1, weak ties
## Scores scaled to unit root mean square, rotated to principal components
## Stopped after 66 iterations: Stress nearly unchanged (ratio > sratmax)

When implementing a most robut function for computing NMDS plots, the result is quiet the same:

## Run 0 stress 0.117853 
## Run 1 stress 0.1353845 
## Run 2 stress 0.1526092 
## Run 3 stress 0.1274873 
## Run 4 stress 0.1457466 
## Run 5 stress 0.1195488 
## Run 6 stress 0.1561102 
## Run 7 stress 0.1195447 
## Run 8 stress 0.1484464 
## Run 9 stress 0.1262914 
## Run 10 stress 0.1240175 
## Run 11 stress 0.1274872 
## Run 12 stress 0.1314554 
## Run 13 stress 0.1335539 
## Run 14 stress 0.1540295 
## Run 15 stress 0.1316594 
## Run 16 stress 0.1309888 
## Run 17 stress 0.1562589 
## Run 18 stress 0.1218611 
## Run 19 stress 0.1436726 
## Run 20 stress 0.1569773 
## *** No convergence -- monoMDS stopping criteria:
##     19: stress ratio > sratmax
##      1: scale factor of the gradient < sfgrmin
## Warning in ordiplot(x, choices = choices, type = type, display = display, :
## Species scores not available

1.4) Geographical analysis

Communities quickly change their composition across geographical distances:

1.4.1) Mantel correlograms

Mantel statistic is -significantlly- so low, meaning that the correlation between samples dissimilarity and geographical distances is weak.

## 
## Mantel statistic based on Pearson's product-moment correlation 
## 
## Call:
## mantel(xdis = geo_distances_MP_18S, ydis = tb16_tax_occur_ss16509_no_cero.bray) 
## 
## Mantel statistic r: 0.1083 
##       Significance: 0.001 
## 
## Upper quantiles of permutations (null model):
##    90%    95%  97.5%    99% 
## 0.0200 0.0291 0.0359 0.0467 
## Permutation: free
## Number of permutations: 999

Correlograms:

MP_18s_ss16509_mantel_correl_by_1000km<-mantel.correlog(tb16_tax_occur_ss16509_no_cero.bray, D.geo=geo_distances_MP_18S, break.pts=seq(0,20000, by=1000))
plot(MP_18s_ss16509_mantel_correl_by_1000km)

MP_18s_ss16509_mantel_correl_by_100km<-mantel.correlog(tb16_tax_occur_ss16509_no_cero.bray, D.geo=geo_distances_MP_18S, break.pts=seq(0,20000, by=100))
plot(MP_18s_ss16509_mantel_correl_by_100km)

1.5) Abundance vs. occurence

OTUs distribution according to their percentage of occurence and relative abundance.
- red line: OTUs that occur in more than 80% of the samples.
- blue line: regionally abundant OTUs (> 0.1%).
- green line: regionally rare (< 0.001%).

Regionally abundant OTUs (relative abundance over 0.1%):

##     otu_names mean_rabund perc_occur SILVA_consensus
## 1       OTU_1 0.272434150  100.00000            <NA>
## 19      OTU_2 0.079469141  100.00000            <NA>
## 32      OTU_3 0.039445684  100.00000            <NA>
## 60      OTU_5 0.019958478   97.80220            <NA>
## 74      OTU_6 0.017176112  100.00000            <NA>
## 43   OTU_3619 0.017119533  100.00000            <NA>
## 91      OTU_8 0.013883869  100.00000            <NA>
## 102     OTU_9 0.010413234  100.00000            <NA>
## 48      OTU_4 0.009755585   89.01099            <NA>
## 85      OTU_7 0.009328911  100.00000            <NA>
## 62     OTU_51 0.007644182  100.00000            <NA>
## 77     OTU_62 0.006768869  100.00000            <NA>
## 8      OTU_14 0.006130522  100.00000            <NA>
## 7      OTU_13 0.005621309  100.00000            <NA>
## 42     OTU_36 0.005459560   48.35165            <NA>
## 4      OTU_11 0.005357051  100.00000            <NA>
## 51     OTU_43 0.005245224   98.90110            <NA>
## 63     OTU_52 0.005070162  100.00000            <NA>
## 21    OTU_203 0.004783272   81.31868            <NA>
## 88     OTU_75 0.004463766   90.10989            <NA>
## 2      OTU_10 0.004287372   96.70330            <NA>
## 10     OTU_16 0.004263409   94.50549            <NA>
## 9      OTU_15 0.003885327  100.00000            <NA>
## 6      OTU_12 0.003390092   96.70330            <NA>
## 5     OTU_112 0.003313544   84.61538            <NA>
## 75   OTU_6052 0.003268946   84.61538            <NA>
## 28     OTU_27 0.003186407   83.51648            <NA>
## 24     OTU_23 0.003173094   96.70330            <NA>
## 44     OTU_38 0.003160447  100.00000            <NA>
## 97   OTU_8518 0.003129162   86.81319            <NA>
## 40     OTU_35 0.003090555   91.20879            <NA>
## 16     OTU_18 0.002965415   97.80220            <NA>
## 13     OTU_17 0.002817644   97.80220            <NA>
## 84   OTU_6983 0.002793681   82.41758            <NA>
## 33     OTU_30 0.002775709  100.00000            <NA>
## 37     OTU_33 0.002741761   85.71429            <NA>
## 26     OTU_26 0.002640584   97.80220            <NA>
## 29   OTU_2754 0.002637256   98.90110            <NA>
## 25     OTU_24 0.002628603   96.70330            <NA>
## 18     OTU_19 0.002609965   95.60440            <NA>
## 39     OTU_34 0.002569361   93.40659            <NA>
## 22     OTU_21 0.002515444   60.43956            <NA>
## 66   OTU_5345 0.002511451   87.91209            <NA>
## 53     OTU_45 0.002384314   91.20879            <NA>
## 72   OTU_5713 0.002192610   87.91209            <NA>
## 98     OTU_86 0.002167982   97.80220            <NA>
## 34    OTU_303 0.002099421  100.00000            <NA>
## 90     OTU_77 0.002020876   76.92308            <NA>
## 35     OTU_31 0.002017548   91.20879            <NA>
## 78   OTU_6249 0.001911046  100.00000            <NA>
## 52     OTU_44 0.001904389   94.50549            <NA>
## 93   OTU_8015 0.001901061  100.00000            <NA>
## 99   OTU_8731 0.001886417   91.20879            <NA>
## 38   OTU_3305 0.001879095   82.41758            <NA>
## 11   OTU_1666 0.001863785   91.20879            <NA>
## 47   OTU_3997 0.001828506   86.81319            <NA>
## 20     OTU_20 0.001815859   79.12088            <NA>
## 71     OTU_57 0.001789899  100.00000            <NA>
## 31     OTU_29 0.001787237   94.50549            <NA>
## 15    OTU_178 0.001763940   98.90110            <NA>
## 45     OTU_39 0.001755286   78.02198            <NA>
## 30     OTU_28 0.001753955   71.42857            <NA>
## 101  OTU_8904 0.001714017  100.00000            <NA>
## 55     OTU_47 0.001692716   96.70330            <NA>
## 17    OTU_182 0.001624821   95.60440            <NA>
## 65     OTU_53 0.001615502   69.23077            <NA>
## 41    OTU_350 0.001594202   96.70330            <NA>
## 12    OTU_167 0.001550936   78.02198            <NA>
## 50     OTU_42 0.001534960   83.51648            <NA>
## 56     OTU_48 0.001467065   82.41758            <NA>
## 54     OTU_46 0.001455749   86.81319            <NA>
## 27    OTU_269 0.001453752   68.13187            <NA>
## 64   OTU_5214 0.001422468   98.90110            <NA>
## 49     OTU_40 0.001399170   85.71429            <NA>
## 103  OTU_9607 0.001385192   96.70330            <NA>
## 96   OTU_8415 0.001375873  100.00000            <NA>
## 86     OTU_72 0.001367885   95.60440            <NA>
## 61   OTU_5092 0.001357235   82.41758            <NA>
## 95    OTU_836 0.001337932   95.60440            <NA>
## 14    OTU_170 0.001290006   85.71429            <NA>
## 70   OTU_5677 0.001268705   98.90110            <NA>
## 87     OTU_73 0.001235423   19.78022            <NA>
## 3     OTU_101 0.001216786   69.23077            <NA>
## 67     OTU_54 0.001211460   91.20879            <NA>
## 58     OTU_49 0.001192823   89.01099            <NA>
## 68     OTU_55 0.001185501   60.43956            <NA>
## 46    OTU_396 0.001164866  100.00000            <NA>
## 69   OTU_5631 0.001161538   17.58242            <NA>
## 80     OTU_63 0.001151553   74.72527            <NA>
## 76     OTU_61 0.001148890  100.00000            <NA>
## 59    OTU_497 0.001148890   32.96703            <NA>
## 81     OTU_65 0.001136243   71.42857            <NA>
## 36     OTU_32 0.001124262   74.72527            <NA>
## 83     OTU_69 0.001121599   51.64835            <NA>
## 94   OTU_8316 0.001117606   89.01099            <NA>
## 23     OTU_22 0.001110284   87.91209            <NA>
## 89   OTU_7628 0.001098302   52.74725            <NA>
## 57   OTU_4850 0.001060361   90.10989            <NA>
## 73     OTU_59 0.001039060   91.20879            <NA>
## 92     OTU_80 0.001033070   41.75824            <NA>
## 79    OTU_627 0.001025082   98.90110            <NA>
## 100    OTU_89 0.001016429   85.71429            <NA>
## 82   OTU_6798 0.001002450   87.91209            <NA>
##                                                                                                                                                SILVA_classif
## 1                              KC002097.1.1314_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_unidentified_marine_bacterioplankton
## 19                                             KM520635.1.1287_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_bacterium
## 32                                                AACY020285848.922.2246_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_marine_metagenome
## 60            KC001782.1.1355_Bacteria_Actinobacteria_Acidimicrobiia_Acidimicrobiales_OM1_clade_Candidatus_Actinomarina_unidentified_marine_bacterioplankton
## 74                               KC000519.1.1314_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Synechococcus_unidentified_marine_bacterioplankton
## 43                                                  AACY023868415.1.1427_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_marine_metagenome
## 91                                    KC002744.1.1344_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_unidentified_marine_bacterioplankton
## 102                                   KC002796.1.1323_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_2_unidentified_marine_bacterioplankton
## 48                           KJ590614.1.1421_Bacteria_Proteobacteria_Alphaproteobacteria_Rhodobacterales_Rhodobacteraceae_Sulfitobacter_uncultured_bacterium
## 85            KC001931.1.1353_Bacteria_Actinobacteria_Acidimicrobiia_Acidimicrobiales_OM1_clade_Candidatus_Actinomarina_unidentified_marine_bacterioplankton
## 62                                             JX945368.1.1448_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_bacterium
## 77                          KF786428.1.1342_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_SAR11_cluster_alpha_proteobacterium
## 8                                         DQ009267.1.1949_Bacteria_Proteobacteria_Alphaproteobacteria_Rickettsiales_SAR116_clade_uncultured_marine_bacterium
## 7                               JX945365.1.1423_Bacteria_Proteobacteria_Alphaproteobacteria_Rhodobacterales_Rhodobacteraceae_uncultured_uncultured_bacterium
## 42                                    HQ233040.1.1357_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_Prochlorococcus_sp
## 4                     DQ009111.1.2063_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS2b_marine_group_uncultured_marine_bacterium
## 51                                    KC000418.1.1315_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_unidentified_marine_bacterioplankton
## 63                                    KC002212.1.1315_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_unidentified_marine_bacterioplankton
## 21                               KC002165.1.1315_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Synechococcus_unidentified_marine_bacterioplankton
## 88                                               GU061737.1.1446_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Synechococcus_uncultured_bacterium
## 2                         KJ549180.1.1447_Bacteria_Proteobacteria_Alphaproteobacteria_Sphingomonadales_Erythrobacteraceae_Erythrobacter_uncultured_bacterium
## 10                                           AACY020257759.244.1709_Bacteria_Proteobacteria_Alphaproteobacteria_Rickettsiales_SAR116_clade_marine_metagenome
## 9                             EU804112.1.1492_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS5_marine_group_uncultured_bacterium
## 6                               JN986244.1.1428_Bacteria_Proteobacteria_Alphaproteobacteria_Rhodobacterales_Rhodobacteraceae_uncultured_uncultured_bacterium
## 5                                              EU237289.1.1306_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_bacterium
## 75                            EU802327.1.1487_Bacteria_Actinobacteria_Acidimicrobiia_Acidimicrobiales_OM1_clade_Candidatus_Actinomarina_uncultured_bacterium
## 28                            EU802512.1.1493_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS4_marine_group_uncultured_bacterium
## 24                          AACY023498084.1.1233_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS4_marine_group_marine_metagenome
## 44                            KC001705.1.1365_Bacteria_Proteobacteria_Gammaproteobacteria_Oceanospirillales_SAR86_clade_unidentified_marine_bacterioplankton
## 97                               KC002188.1.1314_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Synechococcus_unidentified_marine_bacterioplankton
## 40                            EU804152.1.1492_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS4_marine_group_uncultured_bacterium
## 16              KC001557.1.1292_Bacteria_Proteobacteria_Alphaproteobacteria_Rhodobacterales_Rhodobacteraceae_uncultured_unidentified_marine_bacterioplankton
## 13               EU237459.1.1302_Bacteria_Proteobacteria_Alphaproteobacteria_Rhodospirillales_Rhodospirillaceae_AEGEAN-169_marine_group_uncultured_bacterium
## 84                             KC001872.1.1314_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_unidentified_marine_bacterioplankton
## 33                                                    JN986006.1.1452_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_4_uncultured_bacterium
## 37                                     DQ009141.1.1996_Bacteria_Proteobacteria_Gammaproteobacteria_Oceanospirillales_SAR86_clade_uncultured_marine_bacterium
## 26              KC002130.1.1290_Bacteria_Proteobacteria_Alphaproteobacteria_Rhodobacterales_Rhodobacteraceae_uncultured_unidentified_marine_bacterioplankton
## 29                                    HQ233043.1.1357_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_Prochlorococcus_sp
## 25                                        EU802705.1.1252_Bacteria_Bacteroidetes_Cytophagia_Cytophagales_Flammeovirgaceae_Marinoscillum_uncultured_bacterium
## 18                        KJ549185.1.1449_Bacteria_Proteobacteria_Alphaproteobacteria_Sphingomonadales_Erythrobacteraceae_Erythrobacter_uncultured_bacterium
## 39            FN433299.1.1479_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS2b_marine_group_uncultured_Flavobacteriia_bacterium
## 22                     DQ009121.1.1748_Bacteria_Actinobacteria_Acidimicrobiia_Acidimicrobiales_OM1_clade_Candidatus_Actinomarina_uncultured_marine_bacterium
## 66                               KC002668.1.1343_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Synechococcus_unidentified_marine_bacterioplankton
## 53                                    KC002674.1.1343_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_unidentified_marine_bacterioplankton
## 72                                             JX945368.1.1448_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_bacterium
## 98                                                    JN985994.1.1438_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 34                                                    EU802406.1.1257_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 90             FN433412.1.1496_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS4_marine_group_uncultured_Flavobacteriia_bacterium
## 35                                        AACY020563509.792.2305_Bacteria_Proteobacteria_Gammaproteobacteria_Oceanospirillales_SAR86_clade_marine_metagenome
## 78                                    KC002895.1.1345_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_unidentified_marine_bacterioplankton
## 52                                                  AQSI01000003.54241.55782_Bacteria_Marinimicrobia__SAR406_clade__Marinimicrobia_bacterium_SCGC_AAA298-D23
## 93                                                    EU804784.1.1433_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 99          KF786624.1.1388_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS2b_marine_group_uncultured_Flavobacteriales_bacterium
## 38                                             JN986032.1.1449_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_bacterium
## 11                                    AY664087.1.1207_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_Prochlorococcus_sp
## 47                                             JN986032.1.1449_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_bacterium
## 20             KC003455.1.1350_Bacteria_Proteobacteria_Gammaproteobacteria_Alteromonadales_Alteromonadaceae_Alteromonas_unidentified_marine_bacterioplankton
## 71                                               EU805317.1.1450_Bacteria_Proteobacteria_Alphaproteobacteria_Rickettsiales_SAR116_clade_uncultured_bacterium
## 31                                              EU804109.1.1485_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_NS9_marine_group_uncultured_bacterium
## 15                          JNAU01000004.222174.223638_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_Prochlorococcus_sp._MIT_0601
## 45                     KC000407.1.1363_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_Formosa_unidentified_marine_bacterioplankton
## 30                                    JX105591.1.1377_Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Nocardiaceae_Rhodococcus_uncultured_bacterium
## 101                                                   EU804476.1.1440_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 55                                                    JN986342.1.1465_Bacteria_Proteobacteria_Alphaproteobacteria_Rickettsiales_S25-593_uncultured_bacterium
## 17                         DQ396183.1.1451_Bacteria_Proteobacteria_Alphaproteobacteria_Sphingomonadales_Erythrobacteraceae_Erythrobacter_uncultured_organism
## 65                                       AACY020549891.3846.5359_Bacteria_Proteobacteria_Gammaproteobacteria_Oceanospirillales_SAR86_clade_marine_metagenome
## 41                                    KC002791.1.1322_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_unidentified_marine_bacterioplankton
## 12                                  JN166214.1.1446_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_marine_microorganism
## 50                                              EU804751.1.1482_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_NS7_marine_group_uncultured_bacterium
## 56                                       AACY020562322.3851.5364_Bacteria_Proteobacteria_Gammaproteobacteria_Oceanospirillales_SAR86_clade_marine_metagenome
## 54                                             EU803106.1.1287_Bacteria_Proteobacteria_Deltaproteobacteria_SAR324_clade_Marine_group_B__uncultured_bacterium
## 27                      JQ516674.1.1506_Bacteria_Actinobacteria_Acidimicrobiia_Acidimicrobiales_OM1_clade_Candidatus_Actinomarina_uncultured_actinobacterium
## 64                                                    EF572784.1.1439_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 49          KF786431.1.1388_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS2b_marine_group_uncultured_Flavobacteriales_bacterium
## 103                                                   EU804974.1.1439_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 96                                        GQ346738.1.1322_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_alpha_proteobacterium
## 86                                                         AACY020555764.489.1966_Bacteria_Proteobacteria_Alphaproteobacteria_OCS116_clade_marine_metagenome
## 61                            JX945339.1.1492_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS5_marine_group_uncultured_bacterium
## 95                                             KM520431.1.1266_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_bacterium
## 14                               KC002188.1.1314_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Synechococcus_unidentified_marine_bacterioplankton
## 70                                                    KC294824.1.1401_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 87                        AACY020462030.661.2167_Bacteria_Actinobacteria_Acidimicrobiia_Acidimicrobiales_OM1_clade_Candidatus_Actinomarina_marine_metagenome
## 3                              JX526770.1.1401_Bacteria_Proteobacteria_Gammaproteobacteria_Thiotrichales_Thiotrichaceae_Thiothrix_uncultured_proteobacterium
## 67                                       AACY020481938.3418.4929_Bacteria_Proteobacteria_Gammaproteobacteria_Oceanospirillales_SAR86_clade_marine_metagenome
## 58                                     DQ009125.1.1942_Bacteria_Proteobacteria_Gammaproteobacteria_Oceanospirillales_SAR86_clade_uncultured_marine_bacterium
## 68        FQ032819.21712.23225_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS4_marine_group_uncultured_Flavobacteriia_bacterium
## 46                                                    KC294823.1.1400_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 69                                               JN832945.1.1352_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Synechococcus_uncultured_bacterium
## 80                      JQ013156.1.1423_Bacteria_Proteobacteria_Alphaproteobacteria_Rhodobacterales_Rhodobacteraceae_Ascidiaceihabitans_uncultured_bacterium
## 76                        AACY020490277.719.2228_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS5_marine_group_marine_metagenome
## 59             KC811143.18830.20338_Bacteria_Actinobacteria_Acidimicrobiia_Acidimicrobiales_OM1_clade_Candidatus_Actinomarina_Candidatus_Actinomarina_minuta
## 81                                       DQ009089.1.1878_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_NS9_marine_group_uncultured_marine_bacterium
## 36                          HQ622550.1.1449_Bacteria_Proteobacteria_Alphaproteobacteria_Rhizobiales_Aurantimonadaceae_Fulvimarina_Rhizobiales_bacterium_8047
## 83  ATUR01000005.1108.2578_Bacteria_Proteobacteria_Alphaproteobacteria_Sphingomonadales_Sphingomonadaceae_Sphingopyxis_Sphingopyxis_baekryungensis_DSM_16222
## 94                               KC002188.1.1314_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Synechococcus_unidentified_marine_bacterioplankton
## 23                               JQ032339.1.1400_Bacteria_Proteobacteria_Gammaproteobacteria_Oceanospirillales_Halomonadaceae_Halomonas_uncultured_bacterium
## 89                                    HQ233039.1.1357_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_Prochlorococcus_sp
## 57                                             JX945368.1.1448_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_bacterium
## 73          EU795293.31983.33492_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS5_marine_group_uncultured_bacterium_HF0010_31F02
## 92                KC001532.1.1292_Bacteria_Proteobacteria_Alphaproteobacteria_Rhodobacterales_Rhodobacteraceae_Ruegeria_unidentified_marine_bacterioplankton
## 79                                                    EU802825.1.1438_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 100                                                             JN018663.1.1390_Bacteria_Proteobacteria_Gammaproteobacteria_KI89A_clade_uncultured_bacterium
## 82                                    KC003176.1.1343_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_unidentified_marine_bacterioplankton

Number and roportion of regionally abundant OTUs (%):

## [1] 103
## [1] 1.260247


Cosmopolitan OTUs (relative abundance over 0.1% and occurence in more than 80% of samples):

##    otu_names mean_rabund perc_occur SILVA_consensus PhytoREF_consensus
## 1      OTU_1 0.272434150  100.00000            <NA>               <NA>
## 17     OTU_2 0.079469141  100.00000            <NA>               <NA>
## 26     OTU_3 0.039445684  100.00000            <NA>               <NA>
## 61     OTU_6 0.017176112  100.00000            <NA>               <NA>
## 35  OTU_3619 0.017119533  100.00000            <NA>               <NA>
## 72     OTU_8 0.013883869  100.00000            <NA>               <NA>
## 82     OTU_9 0.010413234  100.00000            <NA>               <NA>
## 69     OTU_7 0.009328911  100.00000            <NA>               <NA>
## 52    OTU_51 0.007644182  100.00000            <NA>               <NA>
## 64    OTU_62 0.006768869  100.00000            <NA>               <NA>
## 7     OTU_14 0.006130522  100.00000            <NA>               <NA>
## 6     OTU_13 0.005621309  100.00000            <NA>               <NA>
## 3     OTU_11 0.005357051  100.00000            <NA>               <NA>
## 53    OTU_52 0.005070162  100.00000            <NA>               <NA>
## 8     OTU_15 0.003885327  100.00000            <NA>               <NA>
## 36    OTU_38 0.003160447  100.00000            <NA>               <NA>
## 27    OTU_30 0.002775709  100.00000            <NA>               <NA>
## 28   OTU_303 0.002099421  100.00000            <NA>               <NA>
## 65  OTU_6249 0.001911046  100.00000            <NA>               <NA>
## 73  OTU_8015 0.001901061  100.00000            <NA>               <NA>
## 58    OTU_57 0.001789899  100.00000            <NA>               <NA>
## 81  OTU_8904 0.001714017  100.00000            <NA>               <NA>
## 76  OTU_8415 0.001375873  100.00000            <NA>               <NA>
## 37   OTU_396 0.001164866  100.00000            <NA>               <NA>
## 63    OTU_61 0.001148890  100.00000            <NA>               <NA>
## 42    OTU_43 0.005245224   98.90110            <NA>               <NA>
## 24  OTU_2754 0.002637256   98.90110            <NA>               <NA>
## 13   OTU_178 0.001763940   98.90110            <NA>               <NA>
## 54  OTU_5214 0.001422468   98.90110            <NA>               <NA>
## 57  OTU_5677 0.001268705   98.90110            <NA>               <NA>
## 66   OTU_627 0.001025082   98.90110            <NA>               <NA>
## 50     OTU_5 0.019958478   97.80220            <NA>               <NA>
## 14    OTU_18 0.002965415   97.80220            <NA>               <NA>
## 11    OTU_17 0.002817644   97.80220            <NA>               <NA>
## 22    OTU_26 0.002640584   97.80220            <NA>               <NA>
## 78    OTU_86 0.002167982   97.80220            <NA>               <NA>
## 2     OTU_10 0.004287372   96.70330            <NA>               <NA>
## 5     OTU_12 0.003390092   96.70330            <NA>               <NA>
## 20    OTU_23 0.003173094   96.70330            <NA>               <NA>
## 21    OTU_24 0.002628603   96.70330            <NA>               <NA>
## 46    OTU_47 0.001692716   96.70330            <NA>               <NA>
## 34   OTU_350 0.001594202   96.70330            <NA>               <NA>
## 83  OTU_9607 0.001385192   96.70330            <NA>               <NA>
## 16    OTU_19 0.002609965   95.60440            <NA>               <NA>
## 15   OTU_182 0.001624821   95.60440            <NA>               <NA>
## 70    OTU_72 0.001367885   95.60440            <NA>               <NA>
## 75   OTU_836 0.001337932   95.60440            <NA>               <NA>
## 9     OTU_16 0.004263409   94.50549            <NA>               <NA>
## 43    OTU_44 0.001904389   94.50549            <NA>               <NA>
## 25    OTU_29 0.001787237   94.50549            <NA>               <NA>
## 32    OTU_34 0.002569361   93.40659            <NA>               <NA>
## 33    OTU_35 0.003090555   91.20879            <NA>               <NA>
## 44    OTU_45 0.002384314   91.20879            <NA>               <NA>
## 29    OTU_31 0.002017548   91.20879            <NA>               <NA>
## 79  OTU_8731 0.001886417   91.20879            <NA>               <NA>
## 10  OTU_1666 0.001863785   91.20879            <NA>               <NA>
## 56    OTU_54 0.001211460   91.20879            <NA>               <NA>
## 60    OTU_59 0.001039060   91.20879            <NA>               <NA>
## 71    OTU_75 0.004463766   90.10989            <NA>               <NA>
## 48  OTU_4850 0.001060361   90.10989            <NA>               <NA>
## 39     OTU_4 0.009755585   89.01099            <NA>               <NA>
## 49    OTU_49 0.001192823   89.01099            <NA>               <NA>
## 74  OTU_8316 0.001117606   89.01099            <NA>               <NA>
## 55  OTU_5345 0.002511451   87.91209            <NA>               <NA>
## 59  OTU_5713 0.002192610   87.91209            <NA>               <NA>
## 19    OTU_22 0.001110284   87.91209            <NA>               <NA>
## 67  OTU_6798 0.001002450   87.91209            <NA>               <NA>
## 77  OTU_8518 0.003129162   86.81319            <NA>               <NA>
## 38  OTU_3997 0.001828506   86.81319            <NA>               <NA>
## 45    OTU_46 0.001455749   86.81319            <NA>               <NA>
## 30    OTU_33 0.002741761   85.71429            <NA>               <NA>
## 40    OTU_40 0.001399170   85.71429            <NA>               <NA>
## 12   OTU_170 0.001290006   85.71429            <NA>               <NA>
## 80    OTU_89 0.001016429   85.71429            <NA>               <NA>
## 4    OTU_112 0.003313544   84.61538            <NA>               <NA>
## 62  OTU_6052 0.003268946   84.61538            <NA>               <NA>
## 23    OTU_27 0.003186407   83.51648            <NA>               <NA>
## 41    OTU_42 0.001534960   83.51648            <NA>               <NA>
## 68  OTU_6983 0.002793681   82.41758            <NA>               <NA>
## 31  OTU_3305 0.001879095   82.41758            <NA>               <NA>
## 47    OTU_48 0.001467065   82.41758            <NA>               <NA>
## 51  OTU_5092 0.001357235   82.41758            <NA>               <NA>
## 18   OTU_203 0.004783272   81.31868            <NA>               <NA>

Number and proportion (%) of cosmopolitan OTUs:

## [1] 83
## [1] 1.015539

Number and proportion (%) of rare OTUs:

## [1] 4665
## [1] 57.07818

2.6) Taxonomic composition analysis

2.6.1) Normalized data

No. of OTUs and reads of the rearefied dataset:

## [1] 8173
## [1] 1502319

No. of OTUs and reads of phototrophic groups:

## [1] 1832
## [1] 770960

No. of OTUs and reads of non-phototrophic groups:

## [1] 6341
## [1] 731359


PHOTOTROPHS + HETEROTROPHS

Absolute values

##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae                    128             11                31
## Bolidophyceae                         81              4                41
## Chlorarachniophyceae                  13              2                10
## Chlorodendrophyceae                    2              1                 2
## Cryptophyceae                         40              4                18
## Cyanobacteria                     752531           1211                91
## Dictyochophyceae                    1333             31                88
## Dinophyceae                          256             14                56
## Eustigmatophyceae                    125              6                49
## Mamiellophyceae                      860             16                26
## Pelagophyceae                        399             19                65
## Prasinophyceae_clade-IX              578             18                73
## Prasinophyceae_clade-VII             293             15                34
## Prymnesiophyceae                    8845            314                91
## Pyramimonadaceae                      32              3                11
## Rappemonads                           34              7                24
## Trebouxiophyceae                       2              1                 1
## other_Prasinophyceae                  13              2                10
## other_bacteria                    731359           6341                91
## other_plastids                      5395            153                91


Relative values

##   reads_per_class    OTUs_per_class samples_per_class 
##          100.0000          100.0000          992.3077
##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae           8.520161e-03     0.13458950         34.065934
## Bolidophyceae               5.391664e-03     0.04894164         45.054945
## Chlorarachniophyceae        8.653289e-04     0.02447082         10.989011
## Chlorodendrophyceae         1.331275e-04     0.01223541          2.197802
## Cryptophyceae               2.662550e-03     0.04894164         19.780220
## Cyanobacteria               5.009129e+01    14.81708063        100.000000
## Dictyochophyceae            8.872949e-02     0.37929769         96.703297
## Dinophyceae                 1.704032e-02     0.17129573         61.538462
## Eustigmatophyceae           8.320470e-03     0.07341246         53.846154
## Mamiellophyceae             5.724483e-02     0.19576655         28.571429
## Pelagophyceae               2.655894e-02     0.23247278         71.428571
## Prasinophyceae_clade-IX     3.847385e-02     0.22023737         80.219780
## Prasinophyceae_clade-VII    1.950318e-02     0.18353114         37.362637
## Prymnesiophyceae            5.887564e-01     3.84191851        100.000000
## Pyramimonadaceae            2.130040e-03     0.03670623         12.087912
## Rappemonads                 2.263168e-03     0.08564786         26.373626
## Trebouxiophyceae            1.331275e-04     0.01223541          1.098901
## other_Prasinophyceae        8.653289e-04     0.02447082         10.989011
## other_bacteria              4.868200e+01    77.58473021        100.000000
## other_plastids              3.591115e-01     1.87201762        100.000000



Reads per class vs. OTUs per class:



Reads per class vs. samples in which they occurr:


PHOTOTROPHS

Absolute values

##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae                    128             11                31
## Bolidophyceae                         81              4                41
## Chlorarachniophyceae                  13              2                10
## Chlorodendrophyceae                    2              1                 2
## Cryptophyceae                         40              4                18
## Cyanobacteria                     752531           1211                91
## Dictyochophyceae                    1333             31                88
## Dinophyceae                          256             14                56
## Eustigmatophyceae                    125              6                49
## Mamiellophyceae                      860             16                26
## Pelagophyceae                        399             19                65
## Prasinophyceae_clade-IX              578             18                73
## Prasinophyceae_clade-VII             293             15                34
## Prymnesiophyceae                    8845            314                91
## Pyramimonadaceae                      32              3                11
## Rappemonads                           34              7                24
## Trebouxiophyceae                       2              1                 1
## other_Prasinophyceae                  13              2                10
## other_plastids                      5395            153                91


Relative values

##   reads_per_class    OTUs_per_class samples_per_class 
##          100.0000          100.0000          892.3077
##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae           1.660268e-02     0.60043668         34.065934
## Bolidophyceae               1.050638e-02     0.21834061         45.054945
## Chlorarachniophyceae        1.686209e-03     0.10917031         10.989011
## Chlorodendrophyceae         2.594168e-04     0.05458515          2.197802
## Cryptophyceae               5.188337e-03     0.21834061         19.780220
## Cyanobacteria               9.760960e+01    66.10262009        100.000000
## Dictyochophyceae            1.729013e-01     1.69213974         96.703297
## Dinophyceae                 3.320535e-02     0.76419214         61.538462
## Eustigmatophyceae           1.621355e-02     0.32751092         53.846154
## Mamiellophyceae             1.115492e-01     0.87336245         28.571429
## Pelagophyceae               5.175366e-02     1.03711790         71.428571
## Prasinophyceae_clade-IX     7.497146e-02     0.98253275         80.219780
## Prasinophyceae_clade-VII    3.800457e-02     0.81877729         37.362637
## Prymnesiophyceae            1.147271e+00    17.13973799        100.000000
## Pyramimonadaceae            4.150669e-03     0.16375546         12.087912
## Rappemonads                 4.410086e-03     0.38209607         26.373626
## Trebouxiophyceae            2.594168e-04     0.05458515          1.098901
## other_Prasinophyceae        1.686209e-03     0.10917031         10.989011
## other_plastids              6.997769e-01     8.35152838        100.000000



Reads per class vs. OTUs per class:



Reads per class vs. samples in which they occurr:


Absolute values of cyanobacteria groups richness and abundance:

##                     reads_per_class OTUs_per_class
## Prochlorococcus              688078            979
## Synechococcus                 61311            162
## other_cyanobacteria            3142             70

Relative values of Cyanobacteria groups richness and abundance:

##                     reads_per_class OTUs_per_class
## Prochlorococcus          91.4351701      80.842279
## Synechococcus             8.1473056      13.377374
## Other cyanobacteria       0.4175243       5.780347


PROTISTS

## [1] 621
## [1] 18429
occurrence_counts_phototrophs<-data.table()
nrow(tb16_phototrophs)
## [1] 621
#create a table per group and count in how many samples they occur. 
Dinophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Dinophyceae"),]
Dinophyceae_tb_occur <- Dinophyceae_tb[,1:91]
Dinophyceae_tb_occur_len<-length(Dinophyceae_tb_occur[,colSums(Dinophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Dinophyceae",samples_per_class=Dinophyceae_tb_occur_len))

Prasinophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "other_Prasinophyceae"),]
Prasinophyceae_tb_occur <- Prasinophyceae_tb[,1:91]
Prasinophyceae_tb_occur_len<-length(Prasinophyceae_tb_occur[,colSums(Prasinophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="other_Prasinophyceae",samples_per_class=Prasinophyceae_tb_occur_len))

Chrysophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Chrysophyceae"),]
Chrysophyceae_tb_occur <- Chrysophyceae_tb[,1:91]
Chrysophyceae_tb_occur_len<-length(Chrysophyceae_tb_occur[,colSums(Chrysophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Chrysophyceae",samples_per_class=Chrysophyceae_tb_occur_len))

Pelagophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Pelagophyceae"),]
Pelagophyceae_tb_occur <- Pelagophyceae_tb[,1:91]
Pelagophyceae_tb_occur_len<-length(Pelagophyceae_tb_occur[,colSums(Pelagophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Pelagophyceae",samples_per_class=Pelagophyceae_tb_occur_len))

Dictyochophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Dictyochophyceae"),]
Dictyochophyceae_tb_occur <- Dictyochophyceae_tb[,1:91]
Dictyochophyceae_tb_occur_len<-length(Dictyochophyceae_tb_occur[,colSums(Dictyochophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Dictyochophyceae",samples_per_class=Dictyochophyceae_tb_occur_len))

Cryptophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Cryptophyceae"),]
Cryptophyceae_tb_occur <- Cryptophyceae_tb[,1:91]
Cryptophyceae_tb_occur_len<-length(Cryptophyceae_tb_occur[,colSums(Cryptophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Cryptophyceae",samples_per_class=Cryptophyceae_tb_occur_len))

Bacillariophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Bacillariophyceae"),]
Bacillariophyceae_tb_occur <- Bacillariophyceae_tb[,1:91]
Bacillariophyceae_tb_occur_len<-length(Bacillariophyceae_tb_occur[,colSums(Bacillariophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Bacillariophyceae",samples_per_class=Bacillariophyceae_tb_occur_len))

Chlorarachniophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Chlorarachniophyceae"),]
Chlorarachniophyceae_tb_occur <- Chlorarachniophyceae_tb[,1:91]
Chlorarachniophyceae_tb_occur_len<-length(Chlorarachniophyceae_tb_occur[,colSums(Chlorarachniophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Chlorarachniophyceae",samples_per_class=Chlorarachniophyceae_tb_occur_len))

Bolidophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Bolidophyceae"),]
Bolidophyceae_tb_occur <- Bolidophyceae_tb[,1:91]
Bolidophyceae_tb_occur_len<-length(Bolidophyceae_tb_occur[,colSums(Bolidophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Bolidophyceae",samples_per_class=Bolidophyceae_tb_occur_len))

Pinguiophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Pinguiophyceae"),]
Pinguiophyceae_tb_occur <- Pinguiophyceae_tb[,1:91]
Pinguiophyceae_tb_occur_len<-length(Pinguiophyceae_tb_occur[,colSums(Pinguiophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Pinguiophyceae",samples_per_class=Pinguiophyceae_tb_occur_len))

Prymnesiophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Prymnesiophyceae"),]
Prymnesiophyceae_tb_occur <- Prymnesiophyceae_tb[,1:91]
Prymnesiophyceae_tb_occur_len<-length(Prymnesiophyceae_tb_occur[,colSums(Prymnesiophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Prymnesiophyceae",samples_per_class=Prymnesiophyceae_tb_occur_len))

Mamiellophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Mamiellophyceae"),]
Mamiellophyceae_tb_occur <- Mamiellophyceae_tb[,1:91]
Mamiellophyceae_tb_occur_len<-length(Mamiellophyceae_tb_occur[,colSums(Mamiellophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Mamiellophyceae",samples_per_class=Mamiellophyceae_tb_occur_len))

Eustigmatophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Eustigmatophyceae"),]
Eustigmatophyceae_tb_occur <- Eustigmatophyceae_tb[,1:91]
Eustigmatophyceae_tb_occur_len<-length(Eustigmatophyceae_tb_occur[,colSums(Eustigmatophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Eustigmatophyceae",samples_per_class=Eustigmatophyceae_tb_occur_len))

Chlorophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Chlorophyceae"),]
Chlorophyceae_tb_occur <- Chlorophyceae_tb[,1:91]
Chlorophyceae_tb_occur_len<-length(Chlorophyceae_tb_occur[,colSums(Chlorophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Chlorophyceae",samples_per_class=Chlorophyceae_tb_occur_len))

Ulvophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Ulvophyceae"),]
Ulvophyceae_tb_occur <- Ulvophyceae_tb[,1:91]
Ulvophyceae_tb_occur_len<-length(Ulvophyceae_tb_occur[,colSums(Ulvophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Ulvophyceae",samples_per_class=Ulvophyceae_tb_occur_len))

Raphydophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Raphydophyceae"),]
Raphydophyceae_tb_occur <- Raphydophyceae_tb[,1:91]
Raphydophyceae_tb_occur_len<-length(Raphydophyceae_tb_occur[,colSums(Raphydophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Raphydophyceae",samples_per_class=Raphydophyceae_tb_occur_len))

Trebouxiophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Trebouxiophyceae"),]
Trebouxiophyceae_tb_occur <- Trebouxiophyceae_tb[,1:91]
Trebouxiophyceae_tb_occur_len<-length(Trebouxiophyceae_tb_occur[,colSums(Trebouxiophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Trebouxiophyceae",samples_per_class=Trebouxiophyceae_tb_occur_len))

Phaeophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Phaeophyceae"),]
Phaeophyceae_tb_occur <- Phaeophyceae_tb[,1:91]
Phaeophyceae_tb_occur_len<-length(Phaeophyceae_tb_occur[,colSums(Phaeophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Phaeophyceae",samples_per_class=Phaeophyceae_tb_occur_len))

Phaeothamniophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Phaeothamniophyceae"),]
Phaeothamniophyceae_tb_occur <- Phaeothamniophyceae_tb[,1:91]
Phaeothamniophyceae_tb_occur_len<-length(Phaeothamniophyceae_tb_occur[,colSums(Phaeothamniophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Phaeothamniophyceae",samples_per_class=Phaeothamniophyceae_tb_occur_len))

Xanthophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Xanthophyceae"),]
Xanthophyceae_tb_occur <- Xanthophyceae_tb[,1:91]
Xanthophyceae_tb_occur_len<-length(Xanthophyceae_tb_occur[,colSums(Xanthophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Xanthophyceae",samples_per_class=Xanthophyceae_tb_occur_len))

Chlorodendrophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Chlorodendrophyceae"),]
Chlorodendrophyceae_tb_occur <- Chlorodendrophyceae_tb[,1:91]
Chlorodendrophyceae_tb_occur_len<-length(Chlorodendrophyceae_tb_occur[,colSums(Chlorodendrophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Chlorodendrophyceae",samples_per_class=Chlorodendrophyceae_tb_occur_len))

IncertaeSedis_Archaeplastida_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "IncertaeSedis_Archaeplastida"),]
IncertaeSedis_Archaeplastida_tb_occur <- IncertaeSedis_Archaeplastida_tb[,1:91]
IncertaeSedis_Archaeplastida_tb_occur_len<-length(IncertaeSedis_Archaeplastida_tb_occur[,colSums(IncertaeSedis_Archaeplastida_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="IncertaeSedis_Archaeplastida",samples_per_class=IncertaeSedis_Archaeplastida_tb_occur_len))

Nephroselmidophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Nephroselmidophyceae"),]
Nephroselmidophyceae_tb_occur <- Nephroselmidophyceae_tb[,1:91]
Nephroselmidophyceae_tb_occur_len<-length(Nephroselmidophyceae_tb_occur[,colSums(Nephroselmidophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Nephroselmidophyceae",samples_per_class=Nephroselmidophyceae_tb_occur_len))

Pavlovophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Pavlovophyceae"),]
Pavlovophyceae_tb_occur <- Pavlovophyceae_tb[,1:91]
Pavlovophyceae_tb_occur_len<-length(Pavlovophyceae_tb_occur[,colSums(Pavlovophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Pavlovophyceae",samples_per_class=Pavlovophyceae_tb_occur_len))

Rhodophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Rhodophyceae"),]
Rhodophyceae_tb_occur <- Rhodophyceae_tb[,1:91]
Rhodophyceae_tb_occur_len<-length(Rhodophyceae_tb_occur[,colSums(Rhodophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Rhodophyceae",samples_per_class=Rhodophyceae_tb_occur_len))

Rappemonads_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Rappemonads"),]
Rappemonads_tb_occur <- Rappemonads_tb[,1:91]
Rappemonads_tb_occur_len<-length(Rappemonads_tb_occur[,colSums(Rappemonads_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Rappemonads",samples_per_class=Rappemonads_tb_occur_len))

MOCH_1_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "MOCH_1"),]
MOCH_1_tb_occur <- MOCH_1_tb[,1:91]
MOCH_1_tb_occur_len<-length(MOCH_1_tb_occur[,colSums(MOCH_1_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="MOCH_1",samples_per_class=MOCH_1_tb_occur_len))

MOCH_2_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "MOCH_2"),]
MOCH_2_tb_occur <- MOCH_2_tb[,1:91]
MOCH_2_tb_occur_len<-length(MOCH_2_tb_occur[,colSums(MOCH_2_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="MOCH_2",samples_per_class=MOCH_2_tb_occur_len))

MOCH_5_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "MOCH_5"),]
MOCH_5_tb_occur <- MOCH_5_tb[,1:91]
MOCH_5_tb_occur_len<-length(MOCH_5_tb_occur[,colSums(MOCH_5_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="MOCH_5",samples_per_class=MOCH_5_tb_occur_len))

Prasinophyceae_clade_VII_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Prasinophyceae_clade-VII"),]
Prasinophyceae_clade_VII_tb_occur <- Prasinophyceae_clade_VII_tb[,1:91]
Prasinophyceae_clade_VII_tb_occur_len<-length(Prasinophyceae_clade_VII_tb_occur[,colSums(Prasinophyceae_clade_VII_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Prasinophyceae_clade-VII",samples_per_class=Prasinophyceae_clade_VII_tb_occur_len))

Prasinophyceae_clade_IX_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Prasinophyceae_clade-IX"),]
Prasinophyceae_clade_IX_tb_occur <- Prasinophyceae_clade_IX_tb[,1:91]
Prasinophyceae_clade_IX_tb_occur_len<-length(Prasinophyceae_clade_IX_tb_occur[,colSums(Prasinophyceae_clade_IX_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Prasinophyceae_clade-IX",samples_per_class=Prasinophyceae_clade_IX_tb_occur_len))

Pyramimonadaceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Pyramimonadaceae"),]
Pyramimonadaceae_tb_occur <- Pyramimonadaceae_tb[,1:91]
Pyramimonadaceae_tb_occur_len<-length(Pyramimonadaceae_tb_occur[,colSums(Pyramimonadaceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Pyramimonadaceae",samples_per_class=Pyramimonadaceae_tb_occur_len))

other_plastids_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "other_plastids"),]
other_plastids_tb_occur <- other_plastids_tb[,1:91]
other_plastids_tb_occur_len<-length(other_plastids_tb_occur[,colSums(other_plastids_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="other_plastids",samples_per_class=other_plastids_tb_occur_len))

occurrence_counts_phototrophs
##                            group samples_per_class
##  1:                  Dinophyceae                56
##  2:         other_Prasinophyceae                10
##  3:                Chrysophyceae                 0
##  4:                Pelagophyceae                65
##  5:             Dictyochophyceae                88
##  6:                Cryptophyceae                18
##  7:            Bacillariophyceae                31
##  8:         Chlorarachniophyceae                10
##  9:                Bolidophyceae                41
## 10:               Pinguiophyceae                 0
## 11:             Prymnesiophyceae                91
## 12:              Mamiellophyceae                26
## 13:            Eustigmatophyceae                49
## 14:                Chlorophyceae                 0
## 15:                  Ulvophyceae                 0
## 16:               Raphydophyceae                 0
## 17:             Trebouxiophyceae                 1
## 18:                 Phaeophyceae                 0
## 19:          Phaeothamniophyceae                 0
## 20:                Xanthophyceae                 0
## 21:          Chlorodendrophyceae                 2
## 22: IncertaeSedis_Archaeplastida                 0
## 23:         Nephroselmidophyceae                 0
## 24:               Pavlovophyceae                 0
## 25:                 Rhodophyceae                 0
## 26:                  Rappemonads                24
## 27:                       MOCH_1                 0
## 28:                       MOCH_2                 0
## 29:                       MOCH_5                 0
## 30:     Prasinophyceae_clade-VII                34
## 31:      Prasinophyceae_clade-IX                73
## 32:             Pyramimonadaceae                11
## 33:               other_plastids                91
##                            group samples_per_class
#row.names(occurrence_counts_phototrophs)<-occurrence_counts_phototrophs$group
occurrence_counts_phototrophs<-as.data.frame(occurrence_counts_phototrophs)

Absolute values

##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae                    128             11                31
## Bolidophyceae                         81              4                41
## Chlorarachniophyceae                  13              2                10
## Chlorodendrophyceae                    2              1                 2
## Cryptophyceae                         40              4                18
## Dictyochophyceae                    1333             31                88
## Dinophyceae                          256             14                56
## Eustigmatophyceae                    125              6                49
## Mamiellophyceae                      860             16                26
## Pelagophyceae                        399             19                65
## Prasinophyceae_clade-IX              578             18                73
## Prasinophyceae_clade-VII             293             15                34
## Prymnesiophyceae                    8845            314                91
## Pyramimonadaceae                      32              3                11
## Rappemonads                           34              7                24
## Trebouxiophyceae                       2              1                 1
## other_Prasinophyceae                  13              2                10
## other_plastids                      5395            153                91


Relative values

##   reads_per_class    OTUs_per_class samples_per_class 
##          100.0000          100.0000          792.3077
##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae             0.69455749      1.7713366         34.065934
## Bolidophyceae                 0.43952466      0.6441224         45.054945
## Chlorarachniophyceae          0.07054100      0.3220612         10.989011
## Chlorodendrophyceae           0.01085246      0.1610306          2.197802
## Cryptophyceae                 0.21704922      0.6441224         19.780220
## Dictyochophyceae              7.23316512      4.9919485         96.703297
## Dinophyceae                   1.38911498      2.2544283         61.538462
## Eustigmatophyceae             0.67827880      0.9661836         53.846154
## Mamiellophyceae               4.66655814      2.5764895         28.571429
## Pelagophyceae                 2.16506593      3.0595813         71.428571
## Prasinophyceae_clade-IX       3.13636117      2.8985507         80.219780
## Prasinophyceae_clade-VII      1.58988551      2.4154589         37.362637
## Prymnesiophyceae             47.99500787     50.5636071        100.000000
## Pyramimonadaceae              0.17363937      0.4830918         12.087912
## Rappemonads                   0.18449183      1.1272142         26.373626
## Trebouxiophyceae              0.01085246      0.1610306          1.098901
## other_Prasinophyceae          0.07054100      0.3220612         10.989011
## other_plastids               29.27451300     24.6376812        100.000000



Reads per class vs. OTUs per class:



Reads per class vs. samples in which they occurr:


2.6.2) Non-rarefied data

No. of OTUs and reads of the rearefied dataset:

## [1] 8881
## [1] 4745946

No. of OTUs and reads of phototrophic groups:

## [1] 1952
## [1] 2504586

No. of OTUs and reads of non-phototrophic groups:

## [1] 6929
## [1] 2241360


PHOTOTROPHS + HETEROTROPHS

Absolute values

##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae                    450             14                42
## Bolidophyceae                        271              4                61
## Chlorarachniophyceae                  25              2                16
## Chlorodendrophyceae                    8              1                 5
## Cryptophyceae                        103              6                24
## Cyanobacteria                    2449889           1278                91
## Dictyochophyceae                    4003             31                89
## Dinophyceae                          819             17                73
## Eustigmatophyceae                    369              6                56
## Mamiellophyceae                     1248             16                34
## Pelagophyceae                       1076             19                75
## Prasinophyceae_clade-IX             1785             23                80
## Prasinophyceae_clade-VII             923             16                49
## Prymnesiophyceae                   26832            336                91
## Pyramimonadaceae                      51              3                17
## Rappemonads                          136              7                41
## Trebouxiophyceae                       2              1                 1
## other_Prasinophyceae                  27              2                16
## other_bacteria                   2241360           6929                91
## other_plastids                     16569            170                91


Relative values

##   reads_per_class    OTUs_per_class samples_per_class 
##           100.000           100.000          1146.154
##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae           9.481777e-03     0.15763991         46.153846
## Bolidophyceae               5.710137e-03     0.04503997         67.032967
## Chlorarachniophyceae        5.267654e-04     0.02251999         17.582418
## Chlorodendrophyceae         1.685649e-04     0.01125999          5.494505
## Cryptophyceae               2.170273e-03     0.06755996         26.373626
## Cyanobacteria               5.162067e+01    14.39027137        100.000000
## Dictyochophyceae            8.434567e-02     0.34905979         97.802198
## Dinophyceae                 1.725683e-02     0.19141989         80.219780
## Eustigmatophyceae           7.775057e-03     0.06755996         61.538462
## Mamiellophyceae             2.629613e-02     0.18015989         37.362637
## Pelagophyceae               2.267198e-02     0.21393987         82.417582
## Prasinophyceae_clade-IX     3.761105e-02     0.25897984         87.912088
## Prasinophyceae_clade-VII    1.944818e-02     0.18015989         53.846154
## Prymnesiophyceae            5.653667e-01     3.78335773        100.000000
## Pyramimonadaceae            1.074601e-03     0.03377998         18.681319
## Rappemonads                 2.865604e-03     0.07881995         45.054945
## Trebouxiophyceae            4.214123e-05     0.01125999          1.098901
## other_Prasinophyceae        5.689066e-04     0.02251999         17.582418
## other_bacteria              4.722683e+01    78.02049319        100.000000
## other_plastids              3.491190e-01     1.91419885        100.000000



Reads per class vs. OTUs per class:



Reads per class vs. samples in which they occurr:


PHOTOTROPHS

Absolute values

##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae                    450             14                42
## Bolidophyceae                        271              4                61
## Chlorarachniophyceae                  25              2                16
## Chlorodendrophyceae                    8              1                 5
## Cryptophyceae                        103              6                24
## Cyanobacteria                    2449889           1278                91
## Dictyochophyceae                    4003             31                89
## Dinophyceae                          819             17                73
## Eustigmatophyceae                    369              6                56
## Mamiellophyceae                     1248             16                34
## Pelagophyceae                       1076             19                75
## Prasinophyceae_clade-IX             1785             23                80
## Prasinophyceae_clade-VII             923             16                49
## Prymnesiophyceae                   26832            336                91
## Pyramimonadaceae                      51              3                17
## Rappemonads                          136              7                41
## Trebouxiophyceae                       2              1                 1
## other_Prasinophyceae                  27              2                16
## other_plastids                     16569            170                91


Relative values

##   reads_per_class    OTUs_per_class samples_per_class 
##           100.000           100.000          1046.154
##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae           1.796704e-02     0.71721311         46.153846
## Bolidophyceae               1.082015e-02     0.20491803         67.032967
## Chlorarachniophyceae        9.981690e-04     0.10245902         17.582418
## Chlorodendrophyceae         3.194141e-04     0.05122951          5.494505
## Cryptophyceae               4.112456e-03     0.30737705         26.373626
## Cyanobacteria               9.781613e+01    65.47131148        100.000000
## Dictyochophyceae            1.598268e-01     1.58811475         97.802198
## Dinophyceae                 3.270002e-02     0.87090164         80.219780
## Eustigmatophyceae           1.473297e-02     0.30737705         61.538462
## Mamiellophyceae             4.982859e-02     0.81967213         37.362637
## Pelagophyceae               4.296119e-02     0.97336066         82.417582
## Prasinophyceae_clade-IX     7.126926e-02     1.17827869         87.912088
## Prasinophyceae_clade-VII    3.685240e-02     0.81967213         53.846154
## Prymnesiophyceae            1.071315e+00    17.21311475        100.000000
## Pyramimonadaceae            2.036265e-03     0.15368852         18.681319
## Rappemonads                 5.430039e-03     0.35860656         45.054945
## Trebouxiophyceae            7.985352e-05     0.05122951          1.098901
## other_Prasinophyceae        1.078022e-03     0.10245902         17.582418
## other_plastids              6.615465e-01     8.70901639        100.000000



Reads per class vs. OTUs per class:



Reads per class vs. samples in which they occurr:






Absolute values of cyanobacteria groups richness and abundance:

##                     reads_per_class OTUs_per_class
## Prochlorococcus             2287847           1036
## Synechococcus                152047            167
## other_cyanobacteria            9995             75

Relative values of Cyanobacteria groups richness and abundance:

##                     reads_per_class OTUs_per_class
## Prochlorococcus          93.3857411      81.064163
## Synechococcus             6.2062812      13.067293
## Other cyanobacteria       0.4079777       5.868545


PROTISTS

## [1] 674
## [1] 54697

Absolute values

##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae                    450             14                42
## Bolidophyceae                        271              4                61
## Chlorarachniophyceae                  25              2                16
## Chlorodendrophyceae                    8              1                 5
## Cryptophyceae                        103              6                24
## Dictyochophyceae                    4003             31                89
## Dinophyceae                          819             17                73
## Eustigmatophyceae                    369              6                56
## Mamiellophyceae                     1248             16                34
## Pelagophyceae                       1076             19                75
## Prasinophyceae_clade-IX             1785             23                80
## Prasinophyceae_clade-VII             923             16                49
## Prymnesiophyceae                   26832            336                91
## Pyramimonadaceae                      51              3                17
## Rappemonads                          136              7                41
## Trebouxiophyceae                       2              1                 1
## other_Prasinophyceae                  27              2                16
## other_plastids                     16569            170                91


Relative values

##   reads_per_class    OTUs_per_class samples_per_class 
##          100.0000          100.0000          946.1538
##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae            0.822714226      2.0771513         46.153846
## Bolidophyceae                0.495456789      0.5934718         67.032967
## Chlorarachniophyceae         0.045706346      0.2967359         17.582418
## Chlorodendrophyceae          0.014626031      0.1483680          5.494505
## Cryptophyceae                0.188310145      0.8902077         26.373626
## Dictyochophyceae             7.318500101      4.5994065         97.802198
## Dinophyceae                  1.497339891      2.5222552         80.219780
## Eustigmatophyceae            0.674625665      0.8902077         61.538462
## Mamiellophyceae              2.281660786      2.3738872         37.362637
## Pelagophyceae                1.967201126      2.8189911         82.417582
## Prasinophyceae_clade-IX      3.263433095      3.4124629         87.912088
## Prasinophyceae_clade-VII     1.687478289      2.3738872         53.846154
## Prymnesiophyceae            49.055706894     49.8516320        100.000000
## Pyramimonadaceae             0.093240946      0.4451039         18.681319
## Rappemonads                  0.248642522      1.0385757         45.054945
## Trebouxiophyceae             0.003656508      0.1483680          1.098901
## other_Prasinophyceae         0.049362854      0.2967359         17.582418
## other_plastids              30.292337788     25.2225519        100.000000



Reads per class vs. OTUs per class:



Reads per class vs. samples in which they occurr: